Development of a Cloud Computing Based Management Information System for MSMEs
Article Sidebar
-
Cloud Computing, Operational Efficiency, Technology Adoption
Abstract
Micro, Small, and Medium Enterprises (MSMEs) are vital for economic growth in many developing countries, including Indonesia. However, these businesses face significant challenges related to management inefficiencies, limited access to resources, and lack of technological adoption. This study aims to develop a cloud-based Management Information System (MIS) specifically tailored for MSMEs. The system is designed to improve operational efficiency, enhance decision-making, and facilitate better management practices for MSMEs in Indonesia. The research utilizes a design and development approach, incorporating both qualitative and quantitative methods. Data was collected through surveys and interviews with MSME owners and managers to identify their needs and challenges. The MIS was then developed using cloud computing technologies and tested with a sample of MSMEs. The cloud-based MIS successfully streamlined key management processes such as inventory tracking, financial management, and customer relationship management. Users reported increased operational efficiency, easier data access, and better decision-making capabilities. The system proved scalable, allowing MSMEs of different sizes and sectors to benefit from the technology. The study concludes that cloud computing-based MIS can significantly improve the management processes of MSMEs, contributing to their growth and sustainability.
Full text article
References
Ali, D., Levin, A., Abdulkarim, M., Tijjani, U., Ahmed, B., Namalam, F., Oyewole, F., & Dougherty, L. (2020). A cost-effectiveness analysis of traditional and geographic information system-supported microplanning approaches for routine immunization program management in northern Nigeria. Vaccine, 38(6), 1408–1415. https://doi.org/10.1016/j.vaccine.2019.12.002
Arpaci, I. (2019). A hybrid modeling approach for predicting the educational use of mobile cloud computing services in higher education. Computers in Human Behavior, 90, 181–187. https://doi.org/10.1016/j.chb.2018.09.005
Azogu, I., Norta, A., Papper, I., Longo, J., & Draheim, D. (2019). A Framework for the Adoption of Blockchain Technology in Healthcare Information Management Systems: A Case Study of Nigeria. Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance, 310–316. https://doi.org/10.1145/3326365.3326405
Bali, A. S. (2019). An analytical study of applications of human resource information system in modern human resources management. International Journal of Sustainable Agricultural Management and Informatics, 5(4), 216. https://doi.org/10.1504/IJSAMI.2019.104617
Ben Hassen, H., Ayari, N., & Hamdi, B. (2020). A home hospitalization system based on the Internet of things, Fog computing and cloud computing. Informatics in Medicine Unlocked, 20, 100368. https://doi.org/10.1016/j.imu.2020.100368
Buyya, R., Srirama, S. N., Casale, G., Calheiros, R., Simmhan, Y., Varghese, B., Gelenbe, E., Javadi, B., Vaquero, L. M., Netto, M. A. S., Toosi, A. N., Rodriguez, M. A., Llorente, I. M., Vimercati, S. D. C. D., Samarati, P., Milojicic, D., Varela, C., Bahsoon, R., Assuncao, M. D. D., … Shen, H. (2019). A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade. ACM Computing Surveys, 51(5), 1–38. https://doi.org/10.1145/3241737
Da Fonseca, E. P. R., Caldeira, E., Ramos Filho, H. S., Barbosa E Oliveira, L., Pereira, A. C. M., & Vilela, P. S. (2020). Agro 4.0: A data science-based information system for sustainable agroecosystem management. Simulation Modelling Practice and Theory, 102, 102068. https://doi.org/10.1016/j.simpat.2020.102068
Dang, L. M., Piran, Md. J., Han, D., Min, K., & Moon, H. (2019). A Survey on Internet of Things and Cloud Computing for Healthcare. Electronics, 8(7), 768. https://doi.org/10.3390/electronics8070768
Del Río-Rama, M. D. L. C., Ríos-Manríquez, M., Álvarez-García, J., & Sánchez-Fernández, M. D. (2020). An Empowerment Scale Analysis of Mexican MSMEs: Modeling with Covariance Structures. Mathematics, 8(10), 1817. https://doi.org/10.3390/math8101817
Dobroszek, J., Zarzycka, E., Almasan, A., & Circa, C. (2019). Managers’ perception of the management accounting information system in transition countries. Economic Research-Ekonomska Istraživanja, 32(1), 2798–2817. https://doi.org/10.1080/1331677X.2019.1655466
Gao, Q., Guo, S., Liu, X., Manogaran, G., Chilamkurti, N., & Kadry, S. (2020). Simulation analysis of supply chain risk management system based on IoT information platform. Enterprise Information Systems, 14(9–10), 1354–1378. https://doi.org/10.1080/17517575.2019.1644671
Hagen, S. C., Delgado, G., Ingraham, P., Cooke, I., Emery, R., P. Fisk, J., Melendy, L., Olson, T., Patti, S., Rubin, N., Ziniti, B., Chen, H., Salas, W., Elias, P., & Gustafson, D. (2020). Mapping Conservation Management Practices and Outcomes in the Corn Belt Using the Operational Tillage Information System (OpTIS) and the Denitrification–Decomposition (DNDC) Model. Land, 9(11), 408. https://doi.org/10.3390/land9110408
Hsu, T.-C., Yang, H., Chung, Y.-C., & Hsu, C.-H. (2020). A Creative IoT agriculture platform for cloud fog computing. Sustainable Computing: Informatics and Systems, 28, 100285. https://doi.org/10.1016/j.suscom.2018.10.006
Hull, D. M., Lowry, P. B., Gaskin, J. E., & Mirkovski, K. (2019). A storyteller’s guide to problem?based learning for information systems management education. Information Systems Journal, 29(5), 1040–1057. https://doi.org/10.1111/isj.12234
Ibrahim, F., Susanto, H., Haghi, P. K., & Setiana, D. (2020). Shifting Paradigm of Education Landscape in Time of the COVID-19 Pandemic: Revealing of a Digital Education Management Information System. Applied System Innovation, 3(4), 49. https://doi.org/10.3390/asi3040049
Kalashnikov, A., & Sakrutina, E. (2019). “Safety management system” and Significant Plants of Critical Information Infrastructure. IFAC-PapersOnLine, 52(13), 1391–1396. https://doi.org/10.1016/j.ifacol.2019.11.393
Kolditz, O., Rink, K., Nixdorf, E., Fischer, T., Bilke, L., Naumov, D., Liao, Z., & Yue, T. (2019). Environmental Information Systems: Paving the Path for Digitally Facilitated Water Management (Water 4.0). Engineering, 5(5), 828–832. https://doi.org/10.1016/j.eng.2019.08.002
Kumar, M., Sharma, S. C., Goel, A., & Singh, S. P. (2019). A comprehensive survey for scheduling techniques in cloud computing. Journal of Network and Computer Applications, 143, 1–33. https://doi.org/10.1016/j.jnca.2019.06.006
Liew, A. (2019). Enhancing and enabling management control systems through information technology: The essential roles of internal transparency and global transparency. International Journal of Accounting Information Systems, 33, 16–31. https://doi.org/10.1016/j.accinf.2019.03.001
Martins, J., Branco, F., Gonçalves, R., Au-Yong-Oliveira, M., Oliveira, T., Naranjo-Zolotov, M., & Cruz-Jesus, F. (2019). Assessing the success behind the use of education management information systems in higher education. Telematics and Informatics, 38, 182–193. https://doi.org/10.1016/j.tele.2018.10.001
Mavridis, I., & Karatza, H. (2019). Combining containers and virtual machines to enhance isolation and extend functionality on cloud computing. Future Generation Computer Systems, 94, 674–696. https://doi.org/10.1016/j.future.2018.12.035
O’Donovan, P., Gallagher, C., Leahy, K., & O’Sullivan, D. T. J. (2019). A comparison of fog and cloud computing cyber-physical interfaces for Industry 4.0 real-time embedded machine learning engineering applications. Computers in Industry, 110, 12–35. https://doi.org/10.1016/j.compind.2019.04.016
Purwandari, B., Otmen, B., & Kumaralalita, L. (2019). Adoption Factors of E-Marketplace and Instagram for Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. Proceedings of the 2019 2nd International Conference on Data Science and Information Technology, 111–116. https://doi.org/10.1145/3352411.3352453
Rabbani, M., Wang, Y. L., Khoshkangini, R., Jelodar, H., Zhao, R., & Hu, P. (2020). A hybrid machine learning approach for malicious behaviour detection and recognition in cloud computing. Journal of Network and Computer Applications, 151, 102507. https://doi.org/10.1016/j.jnca.2019.102507
Ren, J., Zhang, D., He, S., Zhang, Y., & Li, T. (2020). A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms: Transparent Computing, Mobile Edge Computing, Fog Computing, and Cloudlet. ACM Computing Surveys, 52(6), 1–36. https://doi.org/10.1145/3362031
Sadeghi-Niaraki, A., Jelokhani-Niaraki, M., & Choi, S.-M. (2020). A Volunteered Geographic Information-Based Environmental Decision Support System for Waste Management and Decision Making. Sustainability, 12(15), 6012. https://doi.org/10.3390/su12156012
Shamshirband, S., Fathi, M., Chronopoulos, A. T., Montieri, A., Palumbo, F., & Pescapè, A. (2020). Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues. Journal of Information Security and Applications, 55, 102582. https://doi.org/10.1016/j.jisa.2020.102582
Sharma, B., & Obaidat, M. S. (2020). Comparative analysis of IoT based products, technology and integration of IoT with cloud computing. IET Networks, 9(2), 43–47. https://doi.org/10.1049/iet-net.2019.0180
Singh, M. P., & Roy, M. (2019). A study of sustainability reporting disclosures for manufacturing MSMEs: Evidence from India. International Journal of Entrepreneurship and Small Business, 38(4), 395. https://doi.org/10.1504/IJESB.2019.104135
Soledad Fabito, B., L .Rodriguez, R., O. Trillanes, A., G. Lira, J. I., Z. Estocada, D., & Q. Sta Ana, P. M. (2020). Investigating the Factors influencing the Use of a Learning Management System (LMS): An Extended Information System Success Model (ISSM). 2020 The 4th International Conference on E-Society, E-Education and E-Technology, 42–46. https://doi.org/10.1145/3421682.3421687
Song, Y., Chen, Y., Yu, Z., Huang, S., & Shen, C. (2020). CloudPSS: A high-performance power system simulator based on cloud computing. Energy Reports, 6, 1611–1618. https://doi.org/10.1016/j.egyr.2020.12.028
Stvilia, B., Wu, S., & Lee, D. J. (2019). A framework for researcher participation in Research Information Management Systems. The Journal of Academic Librarianship, 45(3), 195–202. https://doi.org/10.1016/j.acalib.2019.02.014
Subawa, N. S., Widhiasthini, N. W., & Mimaki, C. A. (2020). An Empirical Study of E-Marketplace Acceptance in MSMEs under the Constructs of Effort Expectancy, Social Influence and Facilitating Condition Factors. Proceedings of the 2020 The 6th International Conference on E-Business and Applications, 116–120. https://doi.org/10.1145/3387263.3387288
Ullah, F., & Sepasgozar, S. M. E. (2019). A Study of Information Technology Adoption for Real-Estate Management: A System Dynamic Model. In P. Wu & X. Wang, Innovative Production and Construction (pp. 469–486). WORLD SCIENTIFIC. https://doi.org/10.1142/9789813272491_0027
Wang, D., Yang, D., Zhou, H., Wang, Y., Hong, D., Dong, Q., & Song, S. (2020). A Novel Application of Educational Management Information System based on Micro Frontends. Procedia Computer Science, 176, 1567–1576. https://doi.org/10.1016/j.procs.2020.09.168
Xu, J., Shi, Y., Xie, Y., & Zhao, S. (2019). A BIM-Based construction and demolition waste information management system for greenhouse gas quantification and reduction. Journal of Cleaner Production, 229, 308–324. https://doi.org/10.1016/j.jclepro.2019.04.158
Xu, X., Liu, Q., Luo, Y., Peng, K., Zhang, X., Meng, S., & Qi, L. (2019). A computation offloading method over big data for IoT-enabled cloud-edge computing. Future Generation Computer Systems, 95, 522–533. https://doi.org/10.1016/j.future.2018.12.055
Yu, F., Wang, Q., Li, M., Zhou, H., Liu, K., Zhang, K., Wang, Z., Xu, Q., Xu, C., Pan, Q., & He, J. (2019). Aquarium: An automatic data-processing and experiment information management system for biological macromolecular crystallography beamlines. Journal of Applied Crystallography, 52(2), 472–477. https://doi.org/10.1107/S1600576719001183
Zhong, Z., & Buyya, R. (2020). A Cost-Efficient Container Orchestration Strategy in Kubernetes-Based Cloud Computing Infrastructures with Heterogeneous Resources. ACM Transactions on Internet Technology, 20(2), 1–24. https://doi.org/10.1145/3378447
Authors
Copyright (c) 2025 Andres Villanueva, Carlos Fernandez, Zhang Li
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
